Displaying publications 61 - 80 of 235 in total

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  1. Shukeri WFWM, Ralib AM, Abdulah NZ, Mat-Nor MB
    J Crit Care, 2018 Feb;43:163-168.
    PMID: 28903084 DOI: 10.1016/j.jcrc.2017.09.009
    PURPOSE: To derive a prediction equation for 30-day mortality in sepsis using a multi-marker approach and compare its performance to the Sequential Organ Failure Assessment (SOFA) score.

    METHODS: This study included 159 septic patients admitted to an intensive care unit. Leukocytes count, procalcitonin (PCT), interleukin-6 (IL-6), and paraoxonase (PON) and arylesterase (ARE) activities of PON-1 were assayed from blood obtained on ICU presentation. Logistic regression was used to derive sepsis mortality score (SMS), a prediction equation describing the relationship between biomarkers and 30-day mortality.

    RESULTS: The 30-day mortality rate was 28.9%. The SMS was [еlogit(p)/(1+еlogit(p))]×100; logit(p)=0.74+(0.004×PCT)+(0.001×IL-6)-(0.025×ARE)-(0.059×leukocytes count). The SMC had higher area under the receiver operating characteristic curve (95% Cl) than SOFA score [0.814 (0.736-0.892) vs. 0.767 (0.677-0.857)], but is not statistically significant. When the SMS was added to the SOFA score, prediction of 30-day mortality improved compared to SOFA score used alone [0.845 (0.777-0.899), p=0.022].

    CONCLUSIONS: A sepsis mortality score using baseline leukocytes count, PCT, IL-6 and ARE was derived, which predicted 30-day mortality with very good performance and added significant prognostic information to SOFA score.

    Matched MeSH terms: ROC Curve
  2. Sha HL, Roslani AC, Poh KS
    Colorectal Dis, 2020 10;22(10):1379-1387.
    PMID: 32337794 DOI: 10.1111/codi.15091
    AIM: The Sodergren score was developed to objectively measure the severity of haemorrhoidal symptoms. This study aimed to determine if there was a difference in the Sodergren score between patients who were offered surgery and patients who underwent successful rubber band ligation of internal haemorrhoidal disease and to assess its performance in guiding management.

    METHOD: This is a prospective, observational study. The preintervention Sodergren scores of subjects with internal haemorrhoidal disease were recorded and blinded to the surgeon in charge. Sodergren scores of subjects in the two arms were unblinded and compared at the end of the study.

    RESULTS: The results for 290 patients were available for final analysis. The median scores of those offered surgery and those who underwent successful rubber band ligation differed significantly [4 (interquartile range 3-10) vs 0 (interquartile range 0-4), P = 0.001]. In predicting treatment, the Sodergren score had an area under the receiver operating characteristic curve of 0.735 (95% CI 0.675-0.795).

    CONCLUSION: There is a significant difference in scores between patients who were offered surgery and patients with successful rubber band ligation. Our study suggests that the Sodergren score has an acceptable discrimination in predicting the need for surgery in internal haemorrhoidal disease. We propose that patients with a Sodergren score of 6 or more be considered for upfront surgery. This score could potentially be used to standardize outcomes of future haemorrhoid trials.

    Matched MeSH terms: ROC Curve
  3. Seak CJ, Ng CJ, Yen DH, Wong YC, Hsu KH, Seak JC, et al.
    Am J Emerg Med, 2014 Dec;32(12):1481-4.
    PMID: 25308825 DOI: 10.1016/j.ajem.2014.09.011
    This study aims to evaluate the performance of Simplified Acute Physiology Score II (SAPS II), the Acute Physiology and Chronic Health Evaluation II (APACHE II) score, and the Sequential Organ Failure Assessment (SOFA) score for predicting illness severity and the mortality of adult hepatic portal venous gas (HPVG) patients presenting to the emergency department (ED). This will assist emergency physicians in risk stratification.
    Matched MeSH terms: ROC Curve
  4. Scelo G, Muller DC, Riboli E, Johansson M, Cross AJ, Vineis P, et al.
    Clin Cancer Res, 2018 Nov 15;24(22):5594-5601.
    PMID: 30037816 DOI: 10.1158/1078-0432.CCR-18-1496
    Purpose: Renal cell carcinoma (RCC) has the potential for cure with surgery when diagnosed at an early stage. Kidney injury molecule-1 (KIM-1) has been shown to be elevated in the plasma of RCC patients. We aimed to test whether plasma KIM-1 could represent a means of detecting RCC prior to clinical diagnosis.Experimental Design: KIM-1 concentrations were measured in prediagnostic plasma from 190 RCC cases and 190 controls nested within a population-based prospective cohort study. Cases had entered the cohort up to 5 years before diagnosis, and controls were matched on cases for date of birth, date at blood donation, sex, and country. We applied conditional logistic regression and flexible parametric survival models to evaluate the association between plasma KIM-1 concentrations and RCC risk and survival.Results: The incidence rate ratio (IRR) of RCC for a doubling in KIM-1 concentration was 1.71 [95% confidence interval (CI), 1.44-2.03, P = 4.1 × 10-23], corresponding to an IRR of 63.3 (95% CI, 16.2-246.9) comparing the 80th to the 20th percentiles of the KIM-1 distribution in this sample. Compared with a risk model including known risk factors of RCC (age, sex, country, body mass index, and tobacco smoking status), a risk model additionally including KIM-1 substantially improved discrimination between cases and controls (area under the receiver-operating characteristic curve of 0.8 compared with 0.7). High plasma KIM-1 concentrations were also associated with poorer survival (P = 0.0053).Conclusions: Plasma KIM-1 concentrations could predict RCC incidence up to 5 years prior to diagnosis and were associated with poorer survival. Clin Cancer Res; 24(22); 5594-601. ©2018 AACR.
    Matched MeSH terms: ROC Curve
  5. Saxena N, Hartman M, Yip CH, Bhoo-Pathy N, Khin LW, Taib NA, et al.
    PLoS One, 2012;7(9):e45809.
    PMID: 23029254 DOI: 10.1371/journal.pone.0045809
    Lymph node ratio (LNR, i.e. the ratio of the number of positive nodes to the total number of nodes excised) is reported to be superior to the absolute number of nodes involved (pN stage) in classifying patients at high versus low risk of death following breast cancer. The added prognostic value of LNR over pN in addition to other prognostic factors has never been assessed.
    Matched MeSH terms: ROC Curve
  6. Saokaew S, Kositamongkol C, Charatcharoenwitthaya P, Srivanichakorn W, Washirasaksiri C, Chaiyakunapruk N, et al.
    Medicine (Baltimore), 2020 Dec 11;99(50):e23619.
    PMID: 33327335 DOI: 10.1097/MD.0000000000023619
    Over half of metabolic syndrome (MetS) patients have nonalcoholic fatty liver disease (NAFLD). To prevent its complications, standard routine screening is required, but the human-resource and budgetary implications need to be taken into consideration. This study compared the performances of 4 noninvasive scoring systems in predicting NAFLD in MetS patients. They were the fatty liver index, hepatic steatosis index, lipid accumulation product index, and nonalcoholic fatty liver disease in metabolic syndrome patients scoring system (NAFLD-MS).Scores were determined for 499 MetS patients, including 249 patients in a type 2 diabetes mellitus (T2DM) subgroup. Ultrasonography was used to diagnose NAFLD. The accuracies and performance of the scoring systems were analyzed using published cutoff values, and comparisons were made of their areas under receiver operating characteristic curves, sensitivities, specificities, positive and negative predictive values, and likelihood ratios.NAFLD was detected in 68% of the MetS patients and 77% of the MetS patients with T2DM. According to the areas under receiver operating characteristic curves, fatty liver index and hepatic steatosis index provided better performances in predicting NAFLD. NAFLD-MS provided the highest specificity of 99% among the MetS patients as a whole, and it provided even better accuracy with similar performance when applied to the subgroup of MetS patients with T2DM. The maximum cost avoidance from unnecessary ultrasonography was also reported by using NAFLD-MS. In terms of simplicity and ease of calculation, the lipid accumulation product index and NAFLD-MS are preferred.All 4 scoring systems proved to be acceptable for predicting NAFLD among MetS and T2DM patients in settings where the availability of ultrasonography is limited. NAFLD-MS provided the highest specificity and cost avoidance, and it is simple to use. All 4 systems can help clinicians decide further investigations.
    Matched MeSH terms: ROC Curve
  7. Saokaew S, Kanchanasuwan S, Apisarnthanarak P, Charoensak A, Charatcharoenwitthaya P, Phisalprapa P, et al.
    Liver Int, 2017 Oct;37(10):1535-1543.
    PMID: 28294515 DOI: 10.1111/liv.13413
    BACKGROUND & AIMS: Non-alcoholic fatty liver disease (NAFLD) can progress from simple steatosis to hepatocellular carcinoma. None of tools have been developed specifically for high-risk patients. This study aimed to develop a simple risk scoring to predict NAFLD in patients with metabolic syndrome (MetS).

    METHODS: A total of 509 patients with MetS were recruited. All were diagnosed by clinicians with ultrasonography-confirmed whether they were patients with NAFLD. Patients were randomly divided into derivation (n=400) and validation (n=109) cohort. To develop the risk score, clinical risk indicators measured at the time of recruitment were built by logistic regression. Regression coefficients were transformed into item scores and added up to a total score. A risk scoring scheme was developed from clinical predictors: BMI ≥25, AST/ALT ≥1, ALT ≥40, type 2 diabetes mellitus and central obesity. The scoring scheme was applied in validation cohort to test the performance.

    RESULTS: The scheme explained, by area under the receiver operating characteristic curve (AuROC), 76.8% of being NAFLD with good calibration (Hosmer-Lemeshow χ2 =4.35; P=.629). The positive likelihood ratio of NAFLD in patients with low risk (scores below 3) and high risk (scores 5 and over) were 2.32 (95% CI: 1.90-2.82) and 7.77 (95% CI: 2.47-24.47) respectively. When applied in validation cohort, the score showed good performance with AuROC 76.7%, and illustrated 84%, and 100% certainty in low- and high-risk groups respectively.

    CONCLUSIONS: A simple and non-invasive scoring scheme of five predictors provides good prediction indices for NAFLD in MetS patients. This scheme may help clinicians in order to take further appropriate action.

    Matched MeSH terms: ROC Curve
  8. Sang C, Yan H, Chan WK, Zhu X, Sun T, Chang X, et al.
    Front Med (Lausanne), 2021;8:637652.
    PMID: 33708783 DOI: 10.3389/fmed.2021.637652
    Non-alcoholic fatty liver disease (NAFLD) is one of the main causes of fibrosis. Liver biopsy remains the gold standard for the confirmation of fibrosis in NAFLD patients. Effective and non-invasive diagnosis of advanced fibrosis is essential to disease surveillance and treatment decisions. Herein we used routine medical test markers and logistic regression to differentiate early and advanced fibrosis in NAFLD patients from China, Malaysia, and India (n1 = 540, n2 = 147, and n3 = 97) who were confirmed by liver biopsy. Nine parameters, including age, body mass index, fasting blood glucose, presence of diabetes or impaired fasting glycemia, alanine aminotransferase, γ-glutamyl transferase, triglyceride, and aspartate transaminase/platelet count ratio, were selected by stepwise logistic regression, receiver operating characteristic curve (ROC), and hypothesis testing and were used for model construction. The area under the ROC curve (auROC) of the model was 0.82 for differentiating early and advanced fibrosis (sensitivity = 0.69, when specificity = 0.80) in the discovery set. Its diagnostic ability remained good in the two independent validation sets (auROC = 0.89 and 0.71) and was consistently superior to existing panels such as the FIB-4 and NAFLD fibrosis score. A web-based tool, LiveFbr, was developed for fast access to our model. The new model may serve as an attractive tool for fibrosis classification in NAFLD patients.
    Matched MeSH terms: ROC Curve
  9. Sahu R, Dash SR, Cacha LA, Poznanski RR, Parida S
    J Integr Neurosci, 2020 Mar 30;19(1):1-9.
    PMID: 32259881 DOI: 10.31083/j.jin.2020.01.24
    Electroencephalography is the recording of brain electrical activities that can be used to diagnose brain seizure disorders. By identifying brain activity patterns and their correspondence between symptoms and diseases, it is possible to give an accurate diagnosis and appropriate drug therapy to patients. This work aims to categorize electroencephalography signals on different channels' recordings for classifying and predicting epileptic seizures. The collection of the electroencephalography recordings contained in the dataset attributes 179 information and 11,500 instances. Instances are of five categories, where one is the symptoms of epilepsy seizure. We have used traditional, ensemble methods and deep machine learning techniques highlighting their performance for the epilepsy seizure detection task. One dimensional convolutional neural network, ensemble machine learning techniques like bagging, boosting (AdaBoost, gradient boosting, and XG boosting), and stacking is implemented. Traditional machine learning techniques such as decision tree, random forest, extra tree, ridge classifier, logistic regression, K-Nearest Neighbor, Naive Bayes (gaussian), and Kernel Support Vector Machine (polynomial, gaussian) are used for classifying and predicting epilepsy seizure. Before using ensemble and traditional techniques, we have preprocessed the data set using the Karl Pearson coefficient of correlation to eliminate irrelevant attributes. Further accuracy of classification and prediction of the classifiers are manipulated using k-fold cross-validation methods and represent the Receiver Operating Characteristic Area Under the Curve for each classifier. After sorting and comparing algorithms, we have found the convolutional neural network and extra tree bagging classifiers to have better performance than all other ensemble and traditional classifiers.
    Matched MeSH terms: ROC Curve
  10. Rohani MFM, Yonan SNM, Tagiling N, Zainon WMNW, Udin Y, Nawi NM
    Asian Spine J, 2020 Oct;14(5):629-638.
    PMID: 32213791 DOI: 10.31616/asj.2019.0308
    STUDY DESIGN: Retrospective study.

    PURPOSE: This study aims to semiquantitatively evaluate the standardized uptake value (SUV) of 99mTc-methylene diphosphonate (MDP) radionuclide tracer in the normal vertebrae of breast cancer patients using an integrated single-photon emission computed tomography (SPECT)/computed tomography (CT) scanner.

    OVERVIEW OF LITERATURE: Molecular imaging techniques using gamma cameras and stand-alone SPECT have traditionally been utilized to evaluate metastatic bone diseases. However, these methods lack quantitative analysis capabilities, impeding accurate uptake characterization.

    METHODS: A total of 30 randomly selected female breast cancer patients were enrolled in this study. The SUV mean (SUVmean) and SUV maximum (SUVmax) values for 286 normal vertebrae at the thoracic and lumbar levels were calculated based on the patients' body weight (BW), body surface area (BSA), and lean body mass (LBM). Additionally, 106 degenerative joint disease (DJD) lesions of the spine were also characterized, and both their BW SUVmean and SUVmax values were obtained. A receiver operating characteristic (ROC) curve analysis was then performed to determine the cutoff value of SUV for differentiating DJD from normal vertebrae.

    RESULTS: The mean±standard deviations for the SUVmean and SUVmax in the normal vertebrae displayed a relatively wide variability: 3.92±0.27 and 6.51±0.72 for BW, 1.05±0.07 and 1.75±0.17 for BSA, and 2.70±0.19 and 4.50±0.44 for LBM, respectively. Generally, the SUVmean had a lower coefficient of variation than the SUVmax. For DJD, the mean±standard deviation for the BW SUVmean and SUVmax was 5.26±3.24 and 7.50±4.34, respectively. Based on the ROC curve, no optimal cutoff value was found to differentiate DJD from normal vertebrae.

    CONCLUSIONS: In this study, the SUV of 99mTc-MDP was successfully determined using SPECT/CT. This research provides an approach that could potentially aid in the clinical quantification of radionuclide uptake in normal vertebrae for the management of breast cancer patients.

    Matched MeSH terms: ROC Curve
  11. Rijal OM, Ebrahimian H, Noor NM, Hussin A, Yunus A, Mahayiddin AA
    Comput Math Methods Med, 2015;2015:424970.
    PMID: 25918551 DOI: 10.1155/2015/424970
    A novel procedure using phase congruency is proposed for discriminating some lung disease using chest radiograph. Phase congruency provides information about transitions between adjacent pixels. Abrupt changes of phase congruency values between pixels may suggest a possible boundary or another feature that may be used for discrimination. This property of phase congruency may have potential for deciding between disease present and disease absent where the regions of infection on the images have no obvious shape, size, or configuration. Five texture measures calculated from phase congruency and Gabor were shown to be normally distributed. This gave good indicators of discrimination errors in the form of the probability of Type I Error (δ) and the probability of Type II Error (β). However, since 1 -  δ is the true positive fraction (TPF) and β is the false positive fraction (FPF), an ROC analysis was used to decide on the choice of texture measures. Given that features are normally distributed, for the discrimination between disease present and disease absent, energy, contrast, and homogeneity from phase congruency gave better results compared to those using Gabor. Similarly, for the more difficult problem of discriminating lobar pneumonia and lung cancer, entropy and homogeneity from phase congruency gave better results relative to Gabor.
    Matched MeSH terms: ROC Curve
  12. Razak S, Justine M, Mohan V
    J Exerc Rehabil, 2021 Feb;17(1):52-58.
    PMID: 33728289 DOI: 10.12965/jer.2142026.013
    This cross-sectional study evaluated the relationships between anthropometric and aerobic fitness (rate of perceived exertion [RPE] and predicted maximal oxygen uptake [VO2max]) among 228 participants (age: 23.78±4.42 years). RPE and predicted VO2max were determined during the cycle ergometer exercise test. Data were also obtained for height, weight, body mass index (BMI), hip and waist (WC) circumferences. Data analysis revealed VO2max is correlated with WC (r=-0.571), weight (r=-0.521), waist-to-height ratio (WHtR) (r=-0.516), waist-to-hip ratio (WHR) (r=-0.487), and BMI (r=-0.47) in men, while, in women with WC (r=-0.581), weight (r=-0.571), WHtR (r=-0.545), BMI (r=-0.545), WHR (r=-0.473), and height (r=-0.287) (all P<0.05). Regression analysis showed WC was a significant predictor for VO2max in men and women (r2=32.6% vs. 33.7%). The receiver operating characteristic curve of WC showed 0.786 and 0.831 for men and women, respectively. WC or abdominal obesity is the strongest predictor for VO2max, which is an indicator of aerobic fitness in Malaysian adults.
    Matched MeSH terms: ROC Curve
  13. Ramli SR, Moreira GMSG, Zantow J, Goris MGA, Nguyen VK, Novoselova N, et al.
    PLoS Negl Trop Dis, 2019 01;13(1):e0007131.
    PMID: 30677033 DOI: 10.1371/journal.pntd.0007131
    BACKGROUND: Leptospirosis is the most common zoonotic disease worldwide. The diagnostic performance of a serological test for human leptospirosis is mainly influenced by the antigen used in the test assay. An ideal serological test should cover all serovars of pathogenic leptospires with high sensitivity and specificity and use reagents that are relatively inexpensive to produce and can be used in tropical climates. Peptide-based tests fulfil at least the latter two requirements, and ORFeome phage display has been successfully used to identify immunogenic peptides from other pathogens.

    METHODOLOGY/PRINCIPAL FINDINGS: Two ORFeome phage display libraries of the entire Leptospira spp. genomes from five local strains isolated in Malaysia and seven WHO reference strains were constructed. Subsequently, 18 unique Leptospira peptides were identified in a screen using a pool of sera from patients with acute leptospirosis. Five of these were validated by titration ELISA using different pools of patient or control sera. The diagnostic performance of these five peptides was then assessed against 16 individual sera from patients with acute leptospirosis and 16 healthy donors and was compared to that of two recombinant reference proteins from L. interrogans. This analysis revealed two peptides (SIR16-D1 and SIR16-H1) from the local isolates with good accuracy for the detection of acute leptospirosis (area under the ROC curve: 0.86 and 0.78, respectively; sensitivity: 0.88 and 0.94; specificity: 0.81 and 0.69), which was close to that of the reference proteins LipL32 and Loa22 (area under the ROC curve: 0.91 and 0.80; sensitivity: 0.94 and 0.81; specificity: 0.75 and 0.75).

    CONCLUSIONS/SIGNIFICANCE: This analysis lends further support for using ORFeome phage display to identify pathogen-associated immunogenic peptides, and it suggests that this technique holds promise for the development of peptide-based diagnostics for leptospirosis and, possibly, of vaccines against this pathogen.

    Matched MeSH terms: ROC Curve
  14. Raffiz M, Abdullah JM
    Am J Emerg Med, 2017 Jan;35(1):150-153.
    PMID: 27852525 DOI: 10.1016/j.ajem.2016.09.044
    INTRODUCTION: Bedside ultrasound measurement of optic nerve sheath diameter (ONSD) is emerging as a non-invasive technique to evaluate and predict raised intracranial pressure (ICP). It has been shown in previous literature that ONSD measurement has good correlation with surrogate findings of raised ICP such as clinical and radiological findings suggestive of raised ICP.

    OBJECTIVES: The objective of the study is to find a correlation between sonographic measurements of ONSD value with ICP value measured via the gold standard invasive intracranial ICP catheter, and to find the cut-off value of ONSD measurement in predicting raised ICP, along with its sensitivity and specificity value.

    METHODS: A prospective observational study was performed using convenience sample of 41 adult neurosurgical patients treated in neurosurgical intensive care unit with invasive intracranial pressure monitoring placed in-situ as part of their clinical care. Portable SonoSite ultrasound machine with 7 MHz linear probe were used to measure optic nerve sheath diameter using the standard technique. Simultaneous ICP readings were obtained directly from the invasive monitoring.

    RESULTS: Seventy-five measurements were performed on 41 patients. The non-parametric Spearman correlation test revealed a significant correlation at the 0.01 level between the ICP and ONSD value, with correlation coefficient of 0.820. The receiver operating characteristic curve generated an area under the curve with the value of 0.964, and with standard error of 0.22. From the receiver operating characteristic curve, we found that the ONSD value of 5.205 mm is 95.8% sensitive and 80.4% specific in detecting raised ICP.

    CONCLUSIONS: ONSD value of 5.205 is sensitive and specific in detecting raised ICP. Bedside ultrasound measurement of ONSD is readily learned, and is reproducible and reliable in predicting raised ICP. This non-invasive technique can be a useful adjunct to the current invasive intracranial catheter monitoring, and has wide potential clinical applications in district hospitals, emergency departments and intensive care units.

    Matched MeSH terms: ROC Curve
  15. Quek KF, Chua CB, Razack AH, Low WY, Loh CS
    Int J Urol, 2005 Jan;12(1):39-45.
    PMID: 15661053 DOI: 10.1111/j.1442-2042.2004.00988.x
    The purpose of the present study was to validate the Mandarin version of the International Prostate Symptom Score (Mand-IPSS) in a Malaysian population.
    Matched MeSH terms: ROC Curve
  16. Pszczolkowski S, Manzano-Patrón JP, Law ZK, Krishnan K, Ali A, Bath PM, et al.
    Eur Radiol, 2021 Oct;31(10):7945-7959.
    PMID: 33860831 DOI: 10.1007/s00330-021-07826-9
    OBJECTIVES: To test radiomics-based features extracted from noncontrast CT of patients with spontaneous intracerebral haemorrhage for prediction of haematoma expansion and poor functional outcome and compare them with radiological signs and clinical factors.

    MATERIALS AND METHODS: Seven hundred fifty-four radiomics-based features were extracted from 1732 scans derived from the TICH-2 multicentre clinical trial. Features were harmonised and a correlation-based feature selection was applied. Different elastic-net parameterisations were tested to assess the predictive performance of the selected radiomics-based features using grid optimisation. For comparison, the same procedure was run using radiological signs and clinical factors separately. Models trained with radiomics-based features combined with radiological signs or clinical factors were tested. Predictive performance was evaluated using the area under the receiver operating characteristic curve (AUC) score.

    RESULTS: The optimal radiomics-based model showed an AUC of 0.693 for haematoma expansion and an AUC of 0.783 for poor functional outcome. Models with radiological signs alone yielded substantial reductions in sensitivity. Combining radiomics-based features and radiological signs did not provide any improvement over radiomics-based features alone. Models with clinical factors had similar performance compared to using radiomics-based features, albeit with low sensitivity for haematoma expansion. Performance of radiomics-based features was boosted by incorporating clinical factors, with time from onset to scan and age being the most important contributors for haematoma expansion and poor functional outcome prediction, respectively.

    CONCLUSION: Radiomics-based features perform better than radiological signs and similarly to clinical factors on the prediction of haematoma expansion and poor functional outcome. Moreover, combining radiomics-based features with clinical factors improves their performance.

    KEY POINTS: • Linear models based on CT radiomics-based features perform better than radiological signs on the prediction of haematoma expansion and poor functional outcome in the context of intracerebral haemorrhage. • Linear models based on CT radiomics-based features perform similarly to clinical factors known to be good predictors. However, combining these clinical factors with radiomics-based features increases their predictive performance.

    Matched MeSH terms: ROC Curve
  17. Porwal P, Pachade S, Kokare M, Giancardo L, Mériaudeau F
    Comput Biol Med, 2018 11 01;102:200-210.
    PMID: 30308336 DOI: 10.1016/j.compbiomed.2018.09.028
    Age-related Macular Degeneration (AMD) and Diabetic Retinopathy (DR) are the most prevalent diseases responsible for visual impairment in the world. This work investigates discrimination potential in the texture of color fundus images to distinguish between diseased and healthy cases by avoiding the prior lesion segmentation step. It presents a retinal background characterization approach and explores the potential of Local Tetra Patterns (LTrP) for texture classification of AMD, DR and Normal images. Five different experiments distinguishing between DR - normal, AMD - normal, DR - AMD, pathological - normal and AMD - DR - normal cases were conducted and validated using the proposed approach, and promising results were obtained. For all five experiments, different classifiers namely, AdaBoost, c4.5, logistic regression, naive Bayes, neural network, random forest and support vector machine were tested. We experimented with three public datasets, ARIA, STARE and E-Optha. Further, the performance of LTrP is compared with other texture descriptors, such as local phase quantization, local binary pattern and local derivative pattern. In all cases, the proposed method obtained the area under the receiver operating characteristic curve and f-score values higher than 0.78 and 0.746 respectively. It was found that both performance measures achieve over 0.995 for DR and AMD detection using a random forest classifier. The obtained results suggest that the proposed technique can discriminate retinal disease using texture information and has potential to be an important component for an automated screening solution for retinal images.
    Matched MeSH terms: ROC Curve
  18. Poonual W, Navacharoen N, Kangsanarak J, Namwongprom S, Saokaew S
    Korean J Pediatr, 2017 Nov;60(11):353-358.
    PMID: 29234358 DOI: 10.3345/kjp.2017.60.11.353
    Purpose: To develop and evaluate a simple screening tool to assess hearing loss in newborns. A derived score was compared with the standard clinical practice tool.

    Methods: This cohort study was designed to screen the hearing of newborns using transiently evoked otoacoustic emission and auditory brain stem response, and to determine the risk factors associated with hearing loss of newborns in 3 tertiary hospitals in Northern Thailand. Data were prospectively collected from November 1, 2010 to May 31, 2012. To develop the risk score, clinical-risk indicators were measured by Poisson risk regression. The regression coefficients were transformed into item scores dividing each regression-coefficient with the smallest coefficient in the model, rounding the number to its nearest integer, and adding up to a total score.

    Results: Five clinical risk factors (Craniofacial anomaly, Ototoxicity, Birth weight, family history [Relative] of congenital sensorineural hearing loss, and Apgar score) were included in our COBRA score. The screening tool detected, by area under the receiver operating characteristic curve, more than 80% of existing hearing loss. The positive-likelihood ratio of hearing loss in patients with scores of 4, 6, and 8 were 25.21 (95% confidence interval [CI], 14.69-43.26), 58.52 (95% CI, 36.26-94.44), and 51.56 (95% CI, 33.74-78.82), respectively. This result was similar to the standard tool (The Joint Committee on Infant Hearing) of 26.72 (95% CI, 20.59-34.66).

    Conclusion: A simple screening tool of five predictors provides good prediction indices for newborn hearing loss, which may motivate parents to bring children for further appropriate testing and investigations.

    Matched MeSH terms: ROC Curve
  19. Pitisuttithum P, Chan WK, Piyachaturawat P, Imajo K, Nakajima A, Seki Y, et al.
    BMC Gastroenterol, 2020 Apr 06;20(1):88.
    PMID: 32252638 DOI: 10.1186/s12876-020-01240-z
    BACKGROUND: The Gut and Obesity in Asia (GOASIA) Workgroup was formed to study obesity and gastrointestinal diseases in the Asia Pacific region. We aimed to 1) compare the characteristics of elderly (i.e. age ≥ 60) vs. non-elderly patients with biopsy-proven nonalcoholic fatty liver disease (NAFLD); 2) identify predictors of advanced fibrosis in elderly patients with NAFLD; and 3) assess the performance of non-invasive fibrosis scores in the prediction of advance fibrosis in the elderly population.

    METHODS: We abstracted the data of 1008 patients with NAFLD from nine centers across eight countries. Characteristics of elderly and non-elderly patients with NAFLD were compared using 1:3 sex-matched analysis.

    RESULTS: Of the 1008 patients, 175 were elderly [age 64 (62-67) years], who were matched with 525 non-elderly patients [46 (36-54) years]. Elderly patients were more likely to have advanced fibrosis (35.4% vs. 13.3%; p 

    Matched MeSH terms: ROC Curve
  20. Pijnappel EN, Bhoo-Pathy N, Suniza J, See MH, Tan GH, Yip CH, et al.
    World J Surg, 2014 Dec;38(12):3133-7.
    PMID: 25167896 DOI: 10.1007/s00268-014-2752-3
    In settings with limited resources, sentinel lymph node biopsy (SNB) is only offered to breast cancer patients with small tumors and a low a priori risk of axillary metastases.
    Matched MeSH terms: ROC Curve
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